ABSTRACT
BACKGROUND: The cDNA microarray method offers the first possibility of obtaining a global understanding of biological processes in living organisms, by simultaneous read-outs of tens of thousands of mRNAs. Initial experiments suggest that genes with similar function have similar expression patterns. MATERIAL AND METHODS: Understanding this level of biological complexity will, however, require completely new approaches to data analysis. Computer science methods, such as data mining and knowledge discovery, can synthesize interpretable if-then rules that model the relation between gene expressions and functions and use the rules to classify unknown genes. The huge body of existing biological and medical knowledge makes it necessary to develop methods for extracting knowledge from such repositories. RESULTS: Models of relations between gene expressions and gene functions in a data set from a publicly available source are synthesized semiautomatically and applied to classify unknown genes. Encouraging results have been achieved. The method is applied in the analysis of data from our microarray system which has recently become operational. INTERPRETATION: The principles are of general importance and will be used to evaluate a wide range of complex data sets like decision support in clinical medicine, for situations in which physicians need to handle a large volume of data for each patient.
